Soil-Water-Crop models simulate the combined effect of environment and management on crop growth and can provide important information for crop water management strategies. Efficient use of these models complements experimental research because they provide information faster and require fewer resources compared to experimental studies. However, the tradeoff between simplicity and accuracy often limits the broad application of models. Most mechanistic or deterministic models are suited for research and systems analysis, but tend to be technically demanding and input-intensive, and thus are not easily adopted by practitioners. It was a challenge for us to verify the claim by FAO’s Aquacrop that the model can be used by extension workers etc. (without much model experience) because it needs no (further) calibration (ref. 1). A similar dilemma exists for erosion models; the complex (data demanding) models often do not perform better than the simple ones (Ref. 2).

Models are tools to capture complex agricultural systems. Such systems are socio-technical (Picture 1) and to capture maximum reality many disciplines need to contribute to mutual understanding and a common language. Disciplines ranging from environmental sciences (soil, water, plant) to the social (adoption) and economic sciences (profitable). I have always liked and appreciated working in interdisciplinary teams (Picture 1). Crucial is that not one disciplines feels superior than other disciplines, there must be a win-win sense in the air of cooperation. Ten years of such work in Burkina Faso (through the Antenne Sahelienne) have resulted in an extensive scientific understanding of the functioning of Sahelian villages (Picture 2 and Ref. 1).

In order to develop appropriate land management policies that will stimulate adoption of measures that improve the livelihood of farmers, it is imperative to understand the goals and circumstances of farmers, the range of farming systems they have developed, and the variability in socio-economic factors and trends influencing the dynamics of these systems. A comprehensive analysis of the ecosystem (Picture 1) is needed and comprises aspects of complex ecological-economic systems with not only a bio-physical analysis (Picture 2) of the technical possibilities, but also includes a trade-off analysis of a range of socio-economic objectives and ecological sustainability.

Stakeholder involvement in ecosystem analysis allows inclusion of local knowledge, which is important for sustainable development, and participation studies increase chances to transfer scientific knowledge directly into decision making processes. Therefore, when combining land use optimization models with participatory tools, a broader range of social and technical aspects are taken into account in the development of feasible land use plans to increase the likelihood of adoption of the proposed land use options.

Examples of ecosystem analysis are given in Ref. 1 for Burkina Faso, Ref. 2 for Ethiopia and in the PhD of Bui Tan Yen for north Vietnam, (Pictures 3 & 4)